Calibration of deep probabilistic models with decoupled bayesian neural networks.
Juan MaroñasRoberto ParedesDaniel RamosPublished in: Neurocomputing (2020)
Keyphrases
- probabilistic model
- neural network
- bayesian inference
- bayesian networks
- posterior probability
- belief nets
- graphical models
- back propagation
- camera calibration
- bayesian models
- artificial neural networks
- variational inference
- pattern recognition
- generative model
- probabilistic modeling
- conditional random fields
- latent variables
- conditional probabilities
- deep belief networks
- expectation maximization
- language model
- fuzzy logic
- neural network model
- bayesian learning
- multilayer perceptron
- hidden variables
- genetic algorithm
- neural nets
- posterior distribution
- recurrent neural networks
- focal length
- gaussian processes
- bayesian estimation
- fuzzy systems
- feed forward
- hopfield neural network
- self organizing maps
- fault diagnosis
- maximum likelihood
- high resolution
- pairwise
- hand eye coordination